Behavioral Finance
Behavioral finance studies how people actually make financial decisions, not how rational actors theoretically should.
Classical finance assumes people maximize expected utility, process information correctly, and update beliefs rationally. Behavioral finance notices that people consistently don’t do these things, and tries to understand why.
Some of the documented patterns:
Loss aversion. Losses hurt more than equivalent gains feel good. This leads to holding losing positions too long (avoiding the pain of realizing the loss) and selling winners too early (locking in the gain before it disappears).
Overconfidence. People overestimate their ability to predict markets, pick stocks, and time trades. This leads to excessive trading, which usually destroys returns through fees and bad timing.
Anchoring. The first number you see affects your judgment. If a stock was at 50, it feels “cheap” even if $50 is still overvalued.
Herd behavior. Following the crowd feels safe. This creates bubbles (everyone buying because everyone is buying) and crashes (everyone selling because everyone is selling).
Recency bias. Recent events loom larger than older ones. A market that’s been going up feels like it will keep going up. A market that just crashed feels dangerous.
The practical implication: knowing about these biases doesn’t make you immune to them. But it might help you build systems that counteract them - automatic investing, rebalancing rules, checklists before trading. The goal isn’t to be perfectly rational; it’s to be less irrational than you’d otherwise be.